MilaNLProc/survey-language-technologies huggingface dataset:
Gender: Female 
Age: 60+
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Jewish 
Education: Doctorate or above
Mother's education: High school or below
Father's education: Doctorate or above
Self-assessed socioeconomic status (1-10): 7
Home: Own 
Employment: Employed part time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Homemaker
Father's occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Hobbies: Listen to rock/indie music;Exercise;Use social media;Go to museums and galleries;Listen to jazz;Watch dance or ballet 
Devices used daily: Laptop;Smartphone;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings) 
NLP tools they would find useful: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT 
LLM use cases: Writing (e.g., composing emails);Paraphrasing or finding synonyms;Analyze data;Learning (e.g., explaining complex concepts in simple terms);Collecting references 
Contexts of LLM use: Work;Learning;Personal 
Prompt 1: researching medical issues
Prompt 2: researching legal issues
Prompt 3: asking general questions 
Prompt 4: learning new subject matter
Comments: No, it was clear
Gender: Female 
Age: 60+
Nationality: United States
Ethnicity: Black or African American 
Marital status: Divorced 
First language: English 
Religion: Christian 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 4
Home: Own 
Employment: Retired
Occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Mother's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Listen to jazz;Use social media Read Mystery books, Visit friends or family
Devices used daily: Laptop;Smartphone;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
NLP tools they would find useful: Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
Frequency of LLM use: Rarely
LLMs used: ChatGPT 
LLM use cases: Answering questions about general knowledge 
Contexts of LLM use: Personal 
Prompt 1: What are some creative ways to plan a child's birthday party?
Prompt 2: What exactly is Artificial Intelligence or AI? Are you able to chat with me about religion or ethics?
Gender: Male 
Age: 25-34
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Nothing 
Education: Doctorate or above
Mother's education: Graduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 8
Home: Rent 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Elementary occupations (jobs that involve simple and routine tasks which may require the use of hand-held tools and considerable physical effort)
Father's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Hobbies: Listen to rock/indie music;Exercise 
Devices used daily: Smartphone;Laptop 
NLP tools known: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Spell checker (i.e., correcting misspellings) 
NLP tools used: Grammar checker (i.e., correcting grammar mistakes) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings) 
Frequency of LLM use: Rarely
LLMs used: ChatGPT 
LLM use cases: Proofreading/Editing (e.g., grammar, spelling, structure improvements) 
Contexts of LLM use: School/University 
Prompt 1: summarize my essay
Prompt 2: summarize this email
Prompt 3: what are the economic impacts of tarrifs
Prompt 4: do you think the election was stolen
Prompt 5: how to invest
Prompt 6: when should I buy a house
Gender: Male 
Age: 35-44
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: Undergraduate degree
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 8
Home: Own 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Listen to jazz;Go to the opera;Exercise;Watch dance or ballet 
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools they would find useful: Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT;Grok 
LLM use cases: Paraphrasing or finding synonyms;Learning (e.g., explaining complex concepts in simple terms);Brainstorming 
Contexts of LLM use: Work;Learning;Personal 
Prompt 1: Rewrite the following text in 250 words: "..."
Prompt 2: Summarize this: "..."
Prompt 3: What is the best gift to give my wife this val?
Prompt 4: Go to google trends and send links to news trending on health
Prompt 5: Could the Egyptians have build the pyramids in those times?
Prompt 6: Paraphrase this text, and provide accurate references: "..."
Prompt 7: What is the minimum rating to keep your account active on Amazon Flex?
Prompt 8: How do I check the battery report of my windows laptop?
Prompt 9: Give me top 10 TV shows set in space
Prompt 10: Create a template of a project timeline
Comments: No comment
Gender: Female 
Age: 35-44
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Divorced 
First language: English 
Religion: Christian 
Education: Prefer not to say
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 3
Home: Rent 
Employment: Self-employed full time
Occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Mother's occupation: Homemaker
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Go to museums and galleries;Use social media;Exercise;Visit to stately homes 
Devices used daily: Smartphone;Laptop 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Machine translation (e.g. translate Chinese or Russian into English, and vice versa) 
NLP tools used: Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools they would find useful: Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT 
LLM use cases: Brainstorming;Learning (e.g., explaining complex concepts in simple terms);Get information about current events;Answering questions about general knowledge 
Contexts of LLM use: Entertainment;Learning;Personal 
Comments: No, thanks
Gender: Female 
Age: 35-44
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Nothing 
Education: Undergraduate degree
Mother's education: Graduate degree
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 2
Home: Rent 
Employment: Employed full time
Occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Mother's occupation: Elementary occupations (jobs that involve simple and routine tasks which may require the use of hand-held tools and considerable physical effort)
Father's occupation: Prefer not to say
Hobbies: Use social media 
Devices used daily: Smartphone;Laptop;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings) 
NLP tools they would find useful: Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Every day
LLMs used: ChatGPT;Google Gemini 
LLM use cases: Writing (e.g., composing emails);Answering questions about general knowledge 
Contexts of LLM use: Work;School/University;Entertainment;Learning 
Prompt 1: Write an Instagram caption about the Florida strawberry festival
Prompt 2: Write a Facebook post to help sell Girl Scout cookies
Prompt 3: Please write a customer appreciation post for a Tampa bay hotel.
Prompt 4: Girl Scout cookie promo text ideas
Prompt 5: Valentine’s Day caption ideals for San Antonio hotel
Gender: Male 
Age: 55-60
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Nothing 
Education: Undergraduate degree
Mother's education: Undergraduate degree
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 8
Home: Own 
Employment: Retired
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Hobbies: Listen to classical music;Exercise;Listen to jazz;Listen to rock/indie music 
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools they would find useful: Grammar checker (i.e., correcting grammar mistakes);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
Frequency of LLM use: Rarely
LLM use cases: Generic chatbot conversation;Learning (e.g., explaining complex concepts in simple terms);Answering questions about general knowledge 
Contexts of LLM use: Other (specify) Used mainly when asked to for Prolific Studies.  
Comments: I prefer the views of real people on Reddit or similar.  I don't trust AI to give me the information I need.  I feel the information isn't often well put together for specialised, technical or niche  subjects.  It's better for more generic questions.
Gender: Male 
Age: 45-54
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Prefer not to say
Mother's education: Undergraduate degree
Father's education: Prefer not to say
Self-assessed socioeconomic status (1-10): 8
Home: Own 
Employment: Employed part time
Occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Mother's occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Watch sports 
Devices used daily: Smartphone;Laptop 
NLP tools used: Spell checker (i.e., correcting misspellings);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings) 
Frequency of LLM use: Every day
LLMs used: ChatGPT;Grok 
LLM use cases: Writing (e.g., composing emails);Analyze data;Collecting references;Learning (e.g., explaining complex concepts in simple terms) 
Contexts of LLM use: Work;Personal 
Prompt 1: What is Tesla's current vehicle line up?
Prompt 2: What is Monaco bermuda grass seed?
Prompt 3: How does Monaco compare to Tifway 419 bermuda?
Prompt 4: What  is the part number for the GE psc23ngpcc refrig control board?
Prompt 5: How much are superbowl tickets?
Prompt 6: Where is the superbowl being played this year?
Prompt 7: What will trump do to china with tariffs? 
Prompt 8: Is the next hurricane season supposed to be active?
Prompt 9: When are the rockets playing the lakers again?
Prompt 10: How to repair a GE dishwasher that doesnt heat anymore? What to look for?
Gender: Non-binary 
Age: 35-44
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: High school or below
Father's education: Doctorate or above
Self-assessed socioeconomic status (1-10): 3
Home: Rent 
Employment: Self-employed part time
Occupation: Prefer not to say
Mother's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Watch sports;Other (Please specify) video games
Devices used daily: Smartphone;Other desktop computer
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools they would find useful: Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT 
LLM use cases: Brainstorming;Digital content creation (e.g., creation of social media content);Generate art 
Contexts of LLM use: Work 
Prompt 1: generate empty table with 50 items
Prompt 2: help me generate a script for a youtube video
Prompt 3: generate to-do list with 10 items
Prompt 4: generate to-do list with 10 items
Prompt 5: generate to-do list with 10 items
Gender: Male 
Age: 25-34
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: Undergraduate degree
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 3
Home: Rent 
Employment: Employed full time
Occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts);Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Mother's occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Father's occupation: Armed forces occupations (includes all jobs held by members of the armed forces)
Devices used daily: Smartphone 
NLP tools known: Text-to-Speech (i.e, computers being able to read out loud written language);Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT 
LLM use cases: Solving math or logical problems;Completing assignments;Play games 
Contexts of LLM use: Entertainment;Learning;Personal
Gender: Male 
Age: 60+
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: Graduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 8
Home: Own 
Employment: Self-employed part time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Homemaker
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Listen to rock/indie music;Exercise;Other (Please specify) software development
Devices used daily: Smartphone;Laptop 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools they would find useful: Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT;Microsoft Bing AI 
LLM use cases: Coding;Digital content creation (e.g., creation of social media content);Generate art 
Contexts of LLM use: Personal;Learning;Technical 
Prompt 1: I have used it to generate basic code constructs in different languages to get me started. I used bard to discover what it could do.  It did a really good job.
Prompt 2: I have used it to generate images but that was mostly for fun and playing around with the technology.
Gender: Male 
Age: 60+
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Bereaved 
First language: English 
Religion: Other, please specify. WE are GOD
Education: Graduate degree
Mother's education: High school or below
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 4
Home: Rent 
Employment: Self-employed part time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Watch sports;Use social media;Other (Please specify) home improvement
Devices used daily: Laptop;Smartphone;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
Frequency of LLM use: Rarely
LLMs used: ChatGPT;Other don't know
LLM use cases: Answering questions about general knowledge;Learning (e.g., explaining complex concepts in simple terms) 
Contexts of LLM use: Learning;Work 
Prompt 1: Identities of washington dc plane crash
Prompt 2: flight information for indiana trip
Prompt 3: best route to nj store
Prompt 4: fuel consumption of otter aircraft
Prompt 5: fuel consumption of mohawk aircraft
Prompt 6: did trump promise to lower prices day one and when
Prompt 7: best flight plan from west chester to chatanooga tennessee
Gender: Female 
Age: 45-54
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Nothing 
Education: Graduate degree
Mother's education: Doctorate or above
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 7
Home: Own 
Employment: Employed part time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Visit to stately homes;Exercise;Use social media;Go to museums and galleries;Do arts and crafts 
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools used: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative);Machine translation (e.g. translate Chinese or Russian into English, and vice versa) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT 
LLM use cases: Learning (e.g., explaining complex concepts in simple terms);Answering questions about general knowledge 
Prompt 1: Soup recipes without onions
Prompt 2: soup recipes without gluten
Prompt 3: soup recipes without gluten or onions
Prompt 4: why don't blackbirds use hanging birdfeeders
Prompt 5: how does someone get a job without references
Prompt 6: why don't people care about pigs
Comments: no :-)
Gender: Female 
Age: 25-34
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Cohabitating 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 5
Home: Rent 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Homemaker
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Listen to hiphop and rap;Use social media;Watch sports 
Devices used daily: Laptop;Smartphone;Tablet;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);Text-to-Speech (i.e, computers being able to read out loud written language);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
NLP tools used: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools they would find useful: Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT;Snapchat My AI 
LLM use cases: Writing (e.g., composing emails);Paraphrasing or finding synonyms;Summarizing long texts;Answering questions about general knowledge;Completing assignments;Learning (e.g., explaining complex concepts in simple terms);Brainstorming;Generic chatbot conversation 
Contexts of LLM use: Work;Entertainment;Learning;Personal 
Prompt 1: What is a good shopping list for a family of 5, 3 of them being kids at $200 a week.
Prompt 2: What are major things happening in the world right now?
Prompt 3: What can I make with x y and z for dinner?
Prompt 4: Fact check this for me please.
Prompt 5: I am lonely and would like to talk, I had a bad day.
Prompt 6: What are good keto friendly meals. 
Prompt 7: Give me some fun facts.
Prompt 8: Best places to take kids in Houston.
Prompt 9: Create me a workout playlist.
Prompt 10: What is a good conversation starter?
Comments: Nothing!
Gender: Female 
Age: 45-54
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: Undergraduate degree
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 2
Home: Own 
Employment: Retired
Occupation: Prefer not to say
Mother's occupation: Homemaker
Father's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Hobbies: Listen to rock/indie music;Use social media 
Devices used daily: Smartphone;Other computer, smart tv
NLP tools known: Spell checker (i.e., correcting misspellings) 
NLP tools used: Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools they would find useful: Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Spell checker (i.e., correcting misspellings) 
Frequency of LLM use: Every day
LLMs used: ChatGPT 
LLM use cases: Brainstorming 
Contexts of LLM use: Other (specify) for surveys
Prompt 1: none, they were part of the survey to use them to see if I thought passages were written by AI or a person
Prompt 2: I have none
Prompt 3: I dont remember
Prompt 4: I dont know
Prompt 5: cant go to them because they were part of surveys through Prolific
Gender: Female 
Age: 25-34
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Christian 
Education: Doctorate or above
Mother's education: Undergraduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 7
Home: Own 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Listen to rock/indie music;Exercise;Use social media;Go to museums and galleries;Do arts and crafts;Attend football matches;Watch sports 
Devices used daily: Laptop;Smartphone;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools they would find useful: Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
Frequency of LLM use: Never
Gender: Female 
Age: 18-24
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: Undergraduate degree
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 3
Home: Rent 
Employment: Employed full time
Occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Mother's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Father's occupation: Armed forces occupations (includes all jobs held by members of the armed forces)
Hobbies: Go to museums and galleries;Use social media;Watch sports;Exercise 
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT;Google Gemini 
LLM use cases: Coding;Brainstorming;Writing (e.g., composing emails);Paraphrasing or finding synonyms;Proofreading/Editing (e.g., grammar, spelling, structure improvements) 
Contexts of LLM use: School/University;Personal 
Prompt 1: How do I format a personal statement for graduate programs?
Prompt 2: how long should a personal statement be?
Prompt 3: Give me grad schools with the best psychology programs
Prompt 4: what jobs can you get with a degree in psychology?
Prompt 5: Different fields of psychology 
Prompt 6: how do I ask someone for letter of reccommendation?
Prompt 7: Who should I ask?
Prompt 8: When is the best time to ask for one?
Prompt 9: what does roil mean?
Prompt 10: what is the simple definition of prose 
Comments: no
Gender: Male 
Age: 45-54
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Divorced 
First language: English 
Religion: Nothing 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 7
Home: Own 
Employment: Employed full time
Occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Mother's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Father's occupation: Elementary occupations (jobs that involve simple and routine tasks which may require the use of hand-held tools and considerable physical effort)
Hobbies: Use social media;Listen to rock/indie music 
Devices used daily: Laptop;Smartphone;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools they would find useful: Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Nearly every day
LLMs used: Google Gemini 
LLM use cases: Translation;Generic chatbot conversation;Solving math or logical problems;Get information about current events;Answering questions about general knowledge 
Contexts of LLM use: Work;Entertainment;Personal 
Prompt 1: what's the weather like today
Prompt 2: 50 / what equals 2
Prompt 3: how do you spell extremely
Prompt 4: how many feet are in a yard
Prompt 5: how far away is kalamazoo
Gender: Female 
Age: 45-54
Nationality: United States
Ethnicity: Black or African American 
Marital status: Single 
First language: English 
Religion: Other, please specify. Spiritual
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 3
Home: Rent 
Employment: Self-employed part time
Occupation: Prefer not to say
Mother's occupation: Prefer not to say
Father's occupation: Prefer not to say
Hobbies: Other (Please specify) Reading, watch tv, social media, listen to music
Devices used daily: Laptop;Smartphone;Other internet
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools used: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Grammar checker (i.e., correcting grammar mistakes) 
NLP tools they would find useful: Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
Frequency of LLM use: Rarely
LLMs used: None of these 
LLM use cases: Answering questions about general knowledge 
Contexts of LLM use: Work 
Prompt 1: How much something cost?
Prompt 2: What colors do they come in?
Prompt 3: Can you provide more information on a certain topic?
Comments: I do not have any additional comments about this survey or about AI chatbots.
Gender: Male 
Age: 45-54
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Cohabitating 
First language: English 
Religion: Christian 
Education: High school or below
Mother's education: High school or below
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 4
Home: Rent 
Employment: Not employed, unable to work due to a disability or illness
Occupation: Prefer not to say
Mother's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Father's occupation: Plant and machine operators, and assemblers (those who maintain, operate and monitor industrial and agricultural machinery and equipment)
Hobbies: Listen to rock/indie music;Use social media;Watch sports 
Devices used daily: Laptop;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools they would find useful: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Sometimes
LLM use cases: Brainstorming;Paraphrasing or finding synonyms;Generic chatbot conversation;Generate art;Get information about current events;Answering questions about general knowledge 
Contexts of LLM use: Entertainment;Learning;Personal 
Prompt 1: treadmill  lubrication schdule
Prompt 2: scatter plot request
Prompt 3: how old is aa
Prompt 4: what does a note  mean
Prompt 5: what is mandala
Prompt 6: hiking essentials checklist
Prompt 7: jungle book release year
Prompt 8: ounces in a gallon
Prompt 9: meaning of acquiesce
Prompt 10: pickle calorie count
Comments: none
Gender: Female 
Age: 18-24
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Prefer not to say 
First language: English 
Religion: Nothing 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 9
Home: Prefer not to say 
Employment: Student
Occupation: Prefer not to say
Mother's occupation: Prefer not to say
Father's occupation: Prefer not to say
Hobbies: Listen to hiphop and rap 
Devices used daily: Smartphone;Tablet;Smartwatch 
NLP tools known: Sentiment analysis (e.g. automatically detect if user reviews are positive or negative) 
NLP tools used: Machine translation (e.g. translate Chinese or Russian into English, and vice versa) 
NLP tools they would find useful: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
Frequency of LLM use: Never